oneDNN Apple M2

Apple M2 testing with a Apple MacBook Air (13 h M2 2022) and llvmpipe on Arch rolling via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2209289-NE-ONEDNNAPP07
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A
September 28 2022
  1 Hour, 6 Minutes
B
September 28 2022
  22 Minutes
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September 28 2022
  22 Minutes
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oneDNN Apple M2 Apple M2 testing with a Apple MacBook Air (13 h M2 2022) and llvmpipe on Arch rolling via the Phoronix Test Suite. A: Processor: Apple M2 @ 2.42GHz (4 Cores / 8 Threads), Motherboard: Apple MacBook Air (13 h M2 2022), Memory: 8GB, Disk: 251GB APPLE SSD AP0256Z + 2 x 0GB APPLE SSD AP0256Z, Graphics: llvmpipe, Network: Broadcom Device 4433 + Broadcom Device 5f71 OS: Arch rolling, Kernel: 5.19.0-rc7-asahi-2-1-ARCH (aarch64), Desktop: KDE Plasma 5.25.4, Display Server: X Server 1.21.1.4, OpenGL: 4.5 Mesa 22.1.6 (LLVM 14.0.6 128 bits), Compiler: GCC 12.1.0 + Clang 14.0.6, File-System: ext4, Screen Resolution: 2560x1600 B: Processor: Apple M2 @ 2.42GHz (4 Cores / 8 Threads), Motherboard: Apple MacBook Air (13 h M2 2022), Memory: 8GB, Disk: 251GB APPLE SSD AP0256Z + 2 x 0GB APPLE SSD AP0256Z, Graphics: llvmpipe, Network: Broadcom Device 4433 + Broadcom Device 5f71 OS: Arch rolling, Kernel: 5.19.0-rc7-asahi-2-1-ARCH (aarch64), Desktop: KDE Plasma 5.25.4, Display Server: X Server 1.21.1.4, OpenGL: 4.5 Mesa 22.1.6 (LLVM 14.0.6 128 bits), Compiler: GCC 12.1.0 + Clang 14.0.6, File-System: ext4, Screen Resolution: 2560x1600 C: Processor: Apple M2 @ 2.42GHz (4 Cores / 8 Threads), Motherboard: Apple MacBook Air (13 h M2 2022), Memory: 8GB, Disk: 251GB APPLE SSD AP0256Z + 2 x 0GB APPLE SSD AP0256Z, Graphics: llvmpipe, Network: Broadcom Device 4433 + Broadcom Device 5f71 OS: Arch rolling, Kernel: 5.19.0-rc7-asahi-2-1-ARCH (aarch64), Desktop: KDE Plasma 5.25.4, Display Server: X Server 1.21.1.4, OpenGL: 4.5 Mesa 22.1.6 (LLVM 14.0.6 128 bits), Compiler: GCC 12.1.0 + Clang 14.0.6, File-System: ext4, Screen Resolution: 2560x1600 oneDNN 2.7 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 27.15 |==================================================================== B . 27.21 |==================================================================== C . 27.20 |==================================================================== oneDNN 2.7 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 34.19 |==================================================================== B . 34.13 |==================================================================== C . 34.13 |==================================================================== oneDNN 2.7 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 58.20 |==================================================================== B . 58.33 |==================================================================== C . 58.37 |==================================================================== oneDNN 2.7 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 109.75 |=================================================================== B . 95.11 |========================================================== C . 94.85 |========================================================== oneDNN 2.7 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 42.22 |==================================================================== B . 42.39 |==================================================================== C . 42.40 |==================================================================== oneDNN 2.7 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 267.76 |=================================================================== B . 266.96 |=================================================================== C . 264.62 |================================================================== oneDNN 2.7 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 36.56 |=================================================================== B . 37.23 |==================================================================== C . 36.82 |=================================================================== oneDNN 2.7 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 175.80 |=================================================================== B . 175.51 |=================================================================== C . 175.67 |=================================================================== oneDNN 2.7 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 174.20 |=================================================================== B . 174.55 |=================================================================== C . 174.01 |=================================================================== oneDNN 2.7 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 48.58 |==================================================================== B . 48.54 |==================================================================== C . 48.55 |==================================================================== oneDNN 2.7 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 32230.2 |================================================================== B . 32237.6 |================================================================== C . 32226.7 |================================================================== oneDNN 2.7 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 16519.6 |================================================================== B . 16493.3 |================================================================== C . 16513.1 |================================================================== oneDNN 2.7 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 32236.5 |================================================================== B . 32211.7 |================================================================== C . 32214.7 |================================================================== oneDNN 2.7 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 16505.9 |================================================================== B . 16512.6 |================================================================== C . 16498.2 |================================================================== oneDNN 2.7 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better A . 16.94 |==================================================================== B . 16.93 |==================================================================== C . 16.94 |==================================================================== oneDNN 2.7 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better A . 32230.4 |================================================================== B . 32239.0 |================================================================== C . 32211.4 |================================================================== oneDNN 2.7 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better A . 16512.7 |================================================================== B . 16511.2 |================================================================== C . 16515.5 |================================================================== oneDNN 2.7 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A . 38.67 |==================================================================== B . 38.77 |==================================================================== C . 38.80 |====================================================================